BACKGROUND: Formalin-fixed, paraffin-embedded (FFPE) tissue slides are routinely used in cancer diagnosis, clinical decision-making, and stored in biobanks, but their utilization in Raman spectroscopy-based studies has been limited due to the backgro...
OBJECTIVE: Maximizing safe resection in neuro-oncology has become paramount to improving patient survival and outcomes. Laser interstitial thermal therapy (LITT) offers similar survival benefits to traditional resection, alongside shorter hospital st...
Technological advancements have enabled the extended investigation, development, and application of computational approaches in various domains, including health care. A burgeoning number of diagnostic, predictive, prognostic, and monitoring biomarke...
The development, application, and benchmarking of artificial intelligence (AI) tools to improve diagnosis, prognostication, and therapy in neuro-oncology are increasing at a rapid pace. This Policy Review provides an overview and critical assessment ...
OBJECTIVES: Telomerase reverse transcriptase promoter (pTERT) mutation status plays a key role in making decisions and predicting prognoses for patients with World Health Organization (WHO) grade IV glioma. This study was conducted to assess the valu...
Contrast-MRI scans carry risks associated with the chemical contrast agents. Accurate prediction of enhancement pattern of gliomas has potential in avoiding contrast agent administration to patients. This study aimed to develop a machine learning rad...
MR imaging is central to the assessment of tumor burden and changes over time in neuro-oncology. Several response assessment guidelines have been set forth by the Response Assessment in Pediatric Neuro-Oncology (RAPNO) working groups in different tum...
Clinical cancer research : an official journal of the American Association for Cancer Research
Sep 3, 2024
PURPOSE: Recent artificial intelligence algorithms aided intraoperative decision-making via stimulated Raman histology (SRH) during craniotomy. This study assesses deep learning algorithms for rapid intraoperative diagnosis from SRH images in small s...